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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Rapid and Automated Method for Detecting and Quantifying Adulterations in High-Quality Honey Using Vis-NIRs in Combination with Machine Learning
José Luis P. Calle, Irene Punta-Sánchez, Ana V. González-de-Peredo, et al.
Foods (2023) Vol. 12, Iss. 13, pp. 2491-2491
Open Access | Times Cited: 11

Showing 11 citing articles:

Exploring the role of NIR spectroscopy in quantifying and verifying honey authenticity: A review
Anisha Biswas, Sachin R. Chaudhari
Food Chemistry (2024) Vol. 445, pp. 138712-138712
Closed Access | Times Cited: 17
Machine learning assisted biosensing technology: An emerging powerful tool for improving the intelligence of food safety detection
Zixuan Zhou, Daoming Tian, Yingao Yang, et al.
Current Research in Food Science (2024) Vol. 8, pp. 100679-100679
Open Access | Times Cited: 15
Sugar detection in adulterated honey using hyper-spectral imaging with stacking generalization method
Madhusudan G. Lanjewar, Kamini G. Panchbhai, L. B. Patle
Food Chemistry (2024) Vol. 450, pp. 139322-139322
Closed Access | Times Cited: 7
Quantitative predictions of protein and total flavonoids content in Tartary and common buckwheat using near-infrared spectroscopy and chemometrics
Yue Yu, Yinghui Chai, Zhoutao Li, et al.
Food Chemistry (2024) Vol. 462, pp. 141033-141033
Closed Access | Times Cited: 6
Feature Variable Selection Based on VIS-NIR Spectra and Soil Moisture Content Prediction Model Construction
Nan Zhou, Jin Hong, Bo Song, et al.
Journal of Spectroscopy (2024) Vol. 2024, pp. 1-16
Open Access | Times Cited: 1
Detection of the thaumatin-like protein gene from Brassica rapa var. oleifera in honey with the Proofman-LMTIA method
Wei Yao, Dandan Xu, Dan Zhou, et al.
CyTA - Journal of Food (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 1
High-resolution proteomics and machine-learning identify protein classifiers of honey made by Sicilian black honeybees (Apis mellifera ssp. sicula)
Giulia Biundo, Matteo Calligaris, Margot Lo Pinto, et al.
Food Research International (2024) Vol. 194, pp. 114872-114872
Open Access
Honey Adulteration Detection via Ultraviolet–Visible Spectral Investigation Coupled with Chemometric Analysis
Elisabeta‐Irina Geană, Raluca Isopescu, Corina-Teodora Ciucure, et al.
Foods (2024) Vol. 13, Iss. 22, pp. 3630-3630
Open Access
Detection of tea seed oil adulteration based on near-infrared and Raman spectra information fusion
Jiajun Zan, Hung‐Wing Li, Linfeng Cai, et al.
LWT (2024) Vol. 213, pp. 117064-117064
Open Access
Detecting Honey Adulteration: Advanced Approach Using UF-GC Coupled with Machine Learning
Irene Punta-Sánchez, Tomasz Dymerski, José Luis P. Calle, et al.
Sensors (2024) Vol. 24, Iss. 23, pp. 7481-7481
Open Access
Enhancing Honey Adulteration Detection with Optimal Subspace Wavelength Reduction in Vis-NIR Reflection Spectroscopy
Mokhtar A. Al-Awadhi, Ratnadeep R. Deshmukh
IEEE Access (2023) Vol. 11, pp. 144226-144243
Open Access | Times Cited: 1
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